"Fujitsu’s ground-breaking Artificial Intelligence technology dramatically cuts the time required for an inspection of turbine blades."

Kenneth Lee Kaser
Head of Supply Chain Management Siemens Gamesa

Customer

Siemens Gamesa Renewable Energy was born in April 2017 with the merger of Gamesa Corporación Tecnológica and Siemens Wind Power. It is a respected leader in the renewable energy industry, whose mission is to provide cleaner, more reliable and more affordable energy to society, while creating lasting value for all stakeholders.

Challenge

Siemens must put each of the 5,000 blades it produces annually through a stringent quality assurance process. Any flaws when a blade is in operation could prove catastrophic and could inflict major damage to the company’s reputation. However, manually evaluating UT scanning of each blade takes up to six hours.

Solution

The company wanted a faster solution that wouldn’t compromise on accuracy or safety. Working with long-term partner Fujitsu, together they co-created an Artificial Intelligence solution that could automatically detect flaws through machine learning and deep learning capabilities.

Benefit

Evaluation of each NDT scanning reduced by 80%

Flexible licensing enables the customer to scale as it grows, with minimal upfront investment